The aim of this paper is to present a
method of detection and isolation of intermittent misfiring in power
switches of a three phase inverter feeding an induction machine drive. The
detection and diagnosis procedure is based solely on the output currents of
the inverter flowing into the machine windings. The measured currents are
transformed in the two dimensional frame obtained with the Concordia
transform. The data are then treated by a time-average method. The results
even promising lack of accuracy mainly in the fault isolation step.
To enhance the fault detection and diagnosis by the use of the
information enclosed in the data, a Principal Component Analysis classifier
is applied. The detection of a fault occurrence is made by a two-class
classifier. The isolation is a two-step approach which uses the Linear
Discriminant Analysis; the first is to identify the faulty leg with a
three-class classifier and the second one discriminates the faulty power
switch. Both methods are evaluated with experimental data and pattern
recognition method proves its effectiveness and accuracy in the faulty leg detection and isolation.